The Python SDK for Nextmv
Project description
Nextmv Python SDK
This is the Python SDK for the Nextmv Platform.
Installation
Requires Python >=3.8
. Install using pip
:
pip install nextmv
Usage
The Nextmv Python SDK is used to interact with various parts of the Nextmv Platform:
- Working with a Decision Model: Get to know the functionality for running decision models. These API functions work the same way in any machine (local or hosted).
- Cloud: Interact with the Nextmv Cloud API.
Working with a Decision Model
To run a model, you can use the various helper functionality provided by the SDK. Note that when you create an app that runs locally in your machine, it will run in the same way in a Nextmv Cloud-hosted machine.
Options
Use options to capture parameters (i.e.: configurations) for the run:
import nextmv
options = nextmv.Options(
nextmv.Parameter("str_option", str, "default value", "A string option", required=True),
nextmv.Parameter("int_option", int, 1, "An int option", required=False),
nextmv.Parameter("float_option", float, 1.0, "A float option", required=False),
nextmv.Parameter("bool_option", bool, True, "A bool option", required=True),
)
print(options.str_option)
print(options.int_option)
print(options.float_option)
print(options.bool_option)
print(options.to_dict())
By using options, you are able to pass in the values of the parameters with CLI arguments or environment variables.
$ python main.py --help
usage: main.py [options]
Options for main.py. Use command-line arguments (highest precedence) or environment variables.
optiTo exclude the `markdownlint` rule start and end block, you can use the
following syntax in your markdown file:STR_OPTION
[env var: STR_OPTION] (required) (default: default value) (type: str): A string option
-int_optRemember to replace `Your markdown content here` with your actual markdown
content.(type: int): An int option
-float_option FLOAT_OPTION, --float_option FLOAT_OPTION
[env var: FLOAT_OPTION] (default: 1.0) (type: float): A float option
-bool_option BOOL_OPTION, --bool_option BOOL_OPTION
[env var: BOOL_OPTION] (required) (default: True) (type: bool): A bool option
Input
Capture the input data for the run.
-
Work with
JSON
inputs.import nextmv # Read JSON from stdin. json_input_1 = nextmv.load_local() print(json_input_1.data) # Can also specify JSON format directly, and read from a file. json_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.JSON, path="input.json") print(json_input_2.data)
-
Work with plain,
utf-8
encoded, text inputs.import nextmv # Read text from stdin. text_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT) print(text_input_1.data) # Can also read from a file. text_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.TEXT, path="input.txt") print(text_input_2.data)
-
Work with multiple
CSV
files.import nextmv # Read multiple CSV files from a dir named "input". csv_archive_input_1 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE) print(csv_archive_input_1.data) # Read multiple CSV files from a custom dir. csv_archive_input_2 = nextmv.load_local(input_format=nextmv.InputFormat.CSV_ARCHIVE, path="custom_dir") print(csv_archive_input_2.data)
Logging
The Nextmv platform captures logs via stderr
. Use the provided functionality
to record logs.
import sys
import nextmv
print("0. I do nothing")
nextmv.redirect_stdout()
nextmv.log("1. I log a message to stderr")
print("2. I print a message to stdout")
nextmv.reset_stdout()
print("3. I print another message to stdout")
print("4. I print yet another message to stderr without the logger", file=sys.stderr)
nextmv.log("5. I log a message to stderr using the nextmv module directly")
print("6. I print a message to stdout, again")
After executing it, here are the messages printed to the different streams.
-
stdout
1. I do nothing 2. I print another message to stdout 3. I print a message to stdout, again
-
stderr
1. I log a message to stderr 2. I print a message to stdout 3. I print yet another message to stderr without the logger 4. I log a message to stderr using the nextmv module directly
Output
Write the output data after a run is completed.
-
Work with
JSON
outputs.import nextmv output = nextmv.Output( solution={"foo": "bar"}, statistics=nextmv.Statistics( result=nextmv.ResultStatistics( duration=1.0, value=2.0, custom={"custom": "result_value"}, ), run=nextmv.RunStatistics( duration=3.0, iterations=4, custom={"custom": "run_value"}, ), ), ) # Write to stdout. nextmv.write_local(output) # Write to a file. nextmv.write_local(output, path="output.json")
-
Work with multple
CSV
files.import nextmv output = nextmv.Output( output_format=nextmv.OutputFormat.CSV_ARCHIVE, solution={ "output": [ {"name": "Alice", "age": 30}, {"name": "Bob", "age": 40}, ], }, statistics=nextmv.Statistics( result=nextmv.ResultStatistics( duration=1.0, value=2.0, custom={"custom": "result_value"}, ), run=nextmv.RunStatistics( duration=3.0, iterations=4, custom={"custom": "run_value"}, ), ), ) # Write multiple CSV fiules to a dir named "output". nextmv.write_local(output) # Write multiple CSV files to a custom dir. nextmv.write_local(output, "custom_dir")
Cloud
Before starting:
- Sign up for a Nextmv account.
- Get your API key. Go to Team > API Key.
Visit the docs for more information. Make sure that you have your API key set as an environment variable:
export NEXTMV_API_KEY="<YOUR-API-KEY>"
Additionally, you must have a valid app in Nextmv Cloud.
-
Make a run and get the results.
import os from nextmv.cloud import Application, Client, PollingOptions input = { "defaults": {"vehicles": {"speed": 20}}, "stops": [ { "id": "Nijō Castle", "location": {"lon": 135.748134, "lat": 35.014239}, "quantity": -1, }, { "id": "Kyoto Imperial Palace", "location": {"lon": 135.762057, "lat": 35.025431}, "quantity": -1, }, ], "vehicles": [ { "id": "v2", "capacity": 2, "start_location": {"lon": 135.728898, "lat": 35.039705}, }, ], } client = Client(api_key=os.getenv("NEXTMV_API_KEY")) app = Application(client=client, id="<YOUR-APP-ID>") result = app.new_run_with_result( input=input, instance_id="latest", run_options={"solve.duration": "1s"}, polling_options=PollingOptions(), # Customize the polling options. ) print(result.to_dict())
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